Model comparison
DeepSeek V4 Flash vs Kimi K2.6
Head-to-head evidence from 14 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash #61 (Estimated); Kimi K2.6 #74 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Flash and Kimi K2.6 share 14 comparable benchmark results. 4 of 8 categories are comparable. 8 results are unique to DeepSeek V4 Flash; 37 to Kimi K2.6.
Updated July 23, 2026- Shared results
- 14
- DeepSeek V4 Flash only
- 8
- Kimi K2.6 only
- 37
- Comparable categories
- 4 / 8
Pick DeepSeek V4 Flash if you want the stronger benchmark profile. Kimi K2.6 only becomes the better choice if mathematics is the priority or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 5 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
DeepSeek V4 Flash has the cleaner BenchAlign overall profile here, landing at 58.88 versus 56.79. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Kimi K2.6 is also the more expensive model on tokens at $0.95 input / $4.00 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash. That is roughly 14.3x on output cost alone. Kimi K2.6 is the reasoning model in the pair, while DeepSeek V4 Flash is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. DeepSeek V4 Flash gives you the larger context window at 1M, compared with 256K for Kimi K2.6.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | DeepSeek V4 Flash | Δ | Kimi K2.6 |
|---|---|---|---|
| Math | DeepSeek V4 Flash40.8 | Margin→ 26.3 | Kimi K2.667.1 |
| Agentic | DeepSeek V4 Flash49.1 | Margin→ 24.4 | Kimi K2.673.5 |
| Knowledge | DeepSeek V4 Flash38.8 | Margin→ 3.4 | Kimi K2.642.2 |
| Coding | DeepSeek V4 Flash64.2 | Margin→ 0.2 | Kimi K2.664.4 |
| Multimodal | DeepSeek V4 FlashNot measured | MarginNo overlap | Kimi K2.679.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HMMT Feb 2026
MathA 40.8%B 92.7%Winner: Kimi K2.6Δ 51.9HMMT Feb 2026: DeepSeek V4 Flash scored 40.8%; Kimi K2.6 scored 92.7%. Kimi K2.6 wins this benchmark. - Source ↗
HLE
KnowledgeA 8.1%B 34.7%Winner: Kimi K2.6Δ 26.6HLE: DeepSeek V4 Flash scored 8.1%; Kimi K2.6 scored 34.7%. Kimi K2.6 wins this benchmark. - Source ↗
GPQA
KnowledgeA 71.2%B 90.5%Winner: Kimi K2.6Δ 19.3GPQA: DeepSeek V4 Flash scored 71.2%; Kimi K2.6 scored 90.5%. Kimi K2.6 wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 49.1%B 66.7%Winner: Kimi K2.6Δ 17.6Terminal-Bench 2.0: DeepSeek V4 Flash scored 49.1%; Kimi K2.6 scored 66.7%. Kimi K2.6 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 49.1%B 58.6%Winner: Kimi K2.6Δ 9.5SWE-bench Pro: DeepSeek V4 Flash scored 49.1%; Kimi K2.6 scored 58.6%. Kimi K2.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Flash | Kimi K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash$0.14 input / $0.28 output | Kimi K2.6$0.95 input / $4 output | DeepSeek V4 Flash has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 FlashNot available | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 FlashNot available | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash1M | Kimi K2.6256K | DeepSeek V4 Flash lists the larger context window. |
Benchmark Deep Dive
AgenticKimi K2.6 wins17 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 49.1% | 66.7% | Kimi K2.6 leads |
| MCP AtlasSource | 64% | 55.9% | DeepSeek V4 Flash leads |
| ToolathlonSource | 40.7% | 50% | Kimi K2.6 leads |
| Claw-EvalSource | 57.8% | 62.3% | Kimi K2.6 leads |
| Gert LabsSource | 54.35% | 56.82% | Kimi K2.6 leads |
| BrowseCompSource | — | 83.2% | Not comparable |
| OSWorld-VerifiedSource | — | 73.1% | Not comparable |
| DeepSearchQASource | — | 92.5% | Not comparable |
| WideResearchSource | — | 80.8% | Not comparable |
| AA Agentic IndexSource | — | 30.3% | Not comparable |
| τ²-bench resultsSource | — | 95.9% | Not comparable |
| GDPval-AASource | — | 34.5% | Not comparable |
| GDPval-AASource | — | 1189 | Not comparable |
| APEX-Agents-AASource | — | 28.5% | Not comparable |
| ResearchClawBenchSource | — | 18.0% | Not comparable |
| OSWorld 2.0Source | — | 4.6% | Not comparable |
| terminalBenchHardSource | — | 43.9% | Not comparable |
CodingKimi K2.6 wins10 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.7% | 80.2% | Kimi K2.6 leads |
| SWE-bench ProSource | 49.1% | 58.6% | Kimi K2.6 leads |
| SWE MultilingualSource | 69.7% | 76.7% | Kimi K2.6 leads |
| Terminal-Bench 2.0Source | 49.1% | 66.7% | Kimi K2.6 leads |
| LiveCodeBench v6Source | — | 89.6% | Not comparable |
| SciCodeSource | — | 52.2% | Not comparable |
| Vibe Code BenchSource | — | 37.89% | Not comparable |
| cursorBench31Source | — | 47.6% | Not comparable |
| AA Coding IndexSource | — | 61.8% | Not comparable |
| AA-SciCodeSource | — | 53.5% | Not comparable |
Reasoning4 benchmarks
KnowledgeKimi K2.6 wins12 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| MMLU-ProSource | 83% | — | Not comparable |
| SimpleQASource | 23.1% | — | Not comparable |
| Chinese-SimpleQASource | 71.5% | — | Not comparable |
| GPQASource | 71.2% | 90.5% | Kimi K2.6 leads |
| GPQA-DSource | 71.2% | 90.5% | Kimi K2.6 leads |
| HLESource | 8.1% | 34.7% | Kimi K2.6 leads |
| Artificial Analysis Intelligence IndexSource | — | 44.2% | Not comparable |
| AA-GPQA DiamondSource | — | 91.1% | Not comparable |
| AA-HLESource | — | 35.9% | Not comparable |
| AA-Omniscience IndexSource | — | 6.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 32.8% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 39.3% | Not comparable |
MathKimi K2.6 wins8 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| HMMT Feb 2026Source | 40.8% | 92.7% | Kimi K2.6 leads |
| IMOAnswerBenchSource | 41.9% | — | Not comparable |
| ApexSource | 1.0% | — | Not comparable |
| Apex ShortlistSource | 9.3% | — | Not comparable |
| AIME26Source | — | 96.4% | Not comparable |
| MMAnswerBenchSource | — | 86.0% | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 38.966% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 14.580% | Not comparable |
Multimodal7 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1238 | 1306 | Kimi K2.6 leads |
| MMMU-ProSource | — | 79.4% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 80.1% | Not comparable |
| CharXivSource | — | 80.4% | Not comparable |
| MathVisionSource | — | 87.4% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
| AA-MMMU-ProSource | — | 79.4% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 76.0% | Not comparable |
Frequently Asked Questions (5)
Which is better, DeepSeek V4 Flash or Kimi K2.6?
DeepSeek V4 Flash is ahead on BenchLM's BenchAlign leaderboard, 58.88 to 56.79. The biggest single separator in this matchup is HMMT Feb 2026, where the scores are 40.8% and 92.7%.
Which is better for knowledge tasks, DeepSeek V4 Flash or Kimi K2.6?
Kimi K2.6 has the edge for knowledge tasks in this comparison, averaging 42.2 versus 38.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Flash or Kimi K2.6?
Kimi K2.6 has the edge for coding in this comparison, averaging 64.4 versus 64.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Flash or Kimi K2.6?
Kimi K2.6 has the edge for math in this comparison, averaging 67.1 versus 40.8. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Flash or Kimi K2.6?
Kimi K2.6 has the edge for agentic tasks in this comparison, averaging 73.5 versus 49.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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